Altair® Panopticon™ 2022.0: An Introduction
Panopticon Real Time and Panopticon Streams 2022.0 include usability and performance improvements as well as coding enhancements.
Click here to learn more about Altair Panopticon.
Product Overview Videos
Introduction to Altair® Panopticon™ 2021.2
The Panopticon 2021.2 release incorporates several important new analytics capabilities, including the ability to exclude individual points in time and define multiple non-business hour timespans when analyzing time series data. We have improved several key data visualizations and reporting functions, including easy upload of custom fonts to the server for use in dashboards and PDF reports. Changes to our Streams event processing engine include a new expression builder that makes writing complex expressions for stream processing easier and faster and pluggable Java® transforms that enable use of custom Java code in Streams data pipelines. We have also provided new options to support enterprise deployments, including user session token synchronization across server clusters and the ability to deploy Panopticon in containers on Kubernetes.
Product Overview Videos
Altair Data Analytics Spotlight Series: Visualizing Latency in Realtime
The inability to monitor, investigate, and act on time-sensitive data poses a substantial risk to your trading operations.
Corvil provides unparalleled, best-in-class latency measurements from the edge all the way through your infrastructure, and Altair's real-time streaming and data visualization platform, Panopticon gives you the ability to design visual user interfaces of that data that give you the perspective you need to make insightful, fully informed decisions based on massive amounts of fast-changing data.
Learn how you can leverage Panopticon to remove traditional Corvil session constraints and analyze latency metrics based on symbol, order router, decision strategy, time in force, and any other FIX message field in real-time.
Webinars
The Deep Dive: Practical AI and Data Science for Engineering
Engineers in manufacturing industries can spend as much as 50% of their time acquiring and synthesizing the data required to perform their day-to-day roles. We are convinced that engineers skilled in the use of AI toolsets hold the key to reducing the barrier to successfully capitalize on datasets across a wide range of complex manufacturing problems - from product design and new development to ongoing maintenance. These skills not only enable rapid, data-driven decisions and significantly improve productivity, but also empower engineers to meet the rising demand for an AI-skilled workforce.
Take the next step in unlocking immediate opportunities for your manufacturing operations. Watch our in-depth session, The Deep Dive: Practical AI and Data Science for Engineers.
Webinars
Monetize Your Data Analytics Performance Through Collaboration
How can we take a step back from our current processes and improve them with new Machine Learning tools, or just clever reporting?
In this session, our in-house solutions expert Alyson Kelley discussed how to monetize your current processes by:
- Understanding current trends in data analytics
- Creating strategic alliances within your organization
- Taking advantage of partnerships with current vendors
Webinars
Accelerate Data-driven Smart Operations with Altair Manufacturing Analytics
Explore how Altair enables enterprises to leverage operational data throughout the complete data lifecycle - from shop floor to top floor - with self-service data analytics and machine learning solutions.
Product Overview Videos
Data Science for Engineering
Data science and AI are game-changing technologies for engineering and manufacturing companies. To embrace the need of today and the future for self-service data science and analytics in manufacturing, we need more data engineers to make this all possible.
At Altair, we envision a future where engineers are well equipped to apply data science techniques to derive powerful predictive analysis that transforms the way they operate. There are a plethora of applications for data science in manufacturing - from product design, supply chain optimization, and fault prediction, and preventative maintenance to demand forecasting, and quality assurance. By bridging the gap between the data scientist and engineering roles, your organization can breakdown data silos and extract actionable insights to drive real business value.
The movement has just started. Watch our on-demand webinar to learn more.
Webinars
Monarch Spotlight Series - Data Automation for Mortgage Servicing
Mortgage Servicers using Black Knight face significant challenges around quickly and cost-effectively accessing lending and prepayment risk.
Mortgage Servicers rely on the client and transactional data to evaluate pre-payment risk and execute on investor reporting, loss analysis, and servicing transfers. On platforms like Black Knight MSP, that data is either trapped in static reports or accessible through costly add-ons like BDE. The Altair Mortgage Suite serves as a complement to the mortgage servicing platform by transforming reports into tabular data, applying machine learning, and presenting the data in a visual, easy-to-interpret fashion. Come join our in-house expert with two decades of experience in mortgage servicing Joe Lovati to learn how the Altair Mortgage Suite can bring efficiency to your processes.
Webinars
The Future of Self Service in Data & Analytics
Featuring an enviable lineup including; Frederic de Sibert, Global Head of Investment Banking Services Strategists at Goldman Sachs, Paul Downes, COO at Autovista Group, Kerem Talih, General Manager/CFO at Doğuş Otomotiv and Dr. Mamdouh Refaat, Chief Data Scientist at Altair.
This hour-long webinar is full of insight, guidance, and tips from global businesses that are at various stages of their Data & Analytics journeys.
Webinars
The Future of Data Democratization
Hear from a prestigious panel of experts including David Huguet, Data Lead at SNCF, plus Martijn van Baardwijk, CFO - Continental Europe at Inchcape plc.
Webinars
The Future of Augmented Analytics
Augmented Analytics is being touted as the next frontier in AI’s Evolution with Gartner defining it as “the use of enabling technologies such as machine learning and AI to assist with data preparation, insight generation, and insight explanation to augment how people explore and analyze data”.
Webinars
The Next Generation of Data-Driven Lending
Post COVID-19 and as we navigate our new normal - banking and lending will undoubtedly be transformed. As the economic fallout spreads, financial firms are grappling with a major influx of relief requests from consumer and business customers.
Our panelists discuss whether modern technology, advanced analytics, and a data-driven approach can hold the keys to ensuring banks and fintech leaders continue to scale despite this rapidly evolving credit crisis.
Webinars
How To Achieve Optimized Trading Analytics
In this webinar, we discuss the benefits of analyzing intraday trading risk and performance, the downsides of waiting for end-of-day reports, and the challenges associated with building and using risk compliance dashboards that traders and compliance managers can use effectively to inform trading decisions. We will also demonstrate methods for code-free development of sophisticated Real-Time analytics systems that can be customized to fit the unique requirements of a firm, desk, or trader.
Webinars
Altair Panopticon 2020.0: An Introduction
With Panopticon 2020.0, we have moved to a fully cloud-compatible server-based platform. All functions of the system are handled by the server and are compatible with Linux, Mac, and Windows desktop machines. Panopticon 2020’s new server-side content repository architecture enables automatic sharing of content between servers in multi-server implementations. The platform’s improved user session management tools give admins complete visibility into system utilization, and it now supports Python integration with Apache Arrow serialization. This short video provides a quick overview of the new capabilities of the Panopticon 2020.0 release.
Product Overview Videos
Real-Time Risk Monitoring in Electronic Trading Environments
On the buy-side, risk monitoring helps portfolio managers formulate new strategies for assessing performance. On the sell-side, the same tools enable traders and managers to monitor and analyze all aspects of risk throughout the trading day. Regardless of which asset classes are being traded, the ability to monitor risk on a real-time basis is revolutionizing how risk compliance is accomplished at top tier financial institutions around the world.
In this webinar, we discuss the benefits of analyzing intraday trading risk, the downsides of waiting for end-of-day reports, and the challenges associated with building and using risk compliance dashboards that traders and compliance managers can use effectively to inform trading decisions. We also demonstrate methods for code-free development of sophisticated risk analytics systems that can be customized to fit the unique requirements of a firm, desk, or trader.
Webinars
Real-Time Risk Monitoring in Electronic Trading Environments
On the buy-side, risk monitoring helps portfolio managers formulate new strategies for assessing performance. On the sell-side, the same tools enable traders and managers to monitor and analyze all aspects of risk throughout the trading day. Regardless of which asset classes are being traded, the ability to monitor risk on a real-time basis is revolutionizing how risk compliance is accomplished at top tier financial institutions around the world.
In this webinar, we discuss the benefits of analyzing intraday trading risk, the downsides of waiting for end-of-day reports, and the challenges associated with building and using risk compliance dashboards that traders and compliance managers can use effectively to inform trading decisions. We also demonstrate methods for code-free development of sophisticated risk analytics systems that can be customized to fit the unique requirements of a firm, desk, or trader.
Webinars
Introduction to Panopticon Streams: Stream Processing with No Coding
Panopticon Streams, a stream processing engine built on the popular Apache Kafka platform, enables business users to build sophisticated Kafka data flows with no coding. Streams connects directly to a wide range of streaming and historic information sources, including Kafka, Kx kdb+, Solace, Hadoop and NoSQL sources. Streams supports critical data functions including:
- Streaming Data Prep: Combines multiple real-time streams with historic data sources
- Calculation Engine: Calculates performance metrics based on business needs
- Aggregation Driver: Combines data as needed
- Alerting Engine: Highlights anomalies against user-defined thresholds
- Integration with the Confluent Enterprise Control Center
- Expanded support for IoT environments, including manufacturing, energy/utilities, and transportation/logistics
The engine is designed to be used by people who understand their business problems. They can create their own data flows utilizing data from any number of sources and incorporate joins, aggregations, conflations, calculations, unions, merges, and alerts into their stream processing applications. They can then visualize processed data using Panopticon Visual Analytics and/or output it to Kafka, Kx kdb+, InfluxDb, or any SQL database.
Product Overview Videos
Panopticon Demo: Visualize your Order Book with Full Depth
Panopticon enables traders to visualize their Order Books at full depth. While looking at Top of Book to see the spread across time is useful, traders can’t see what’s happening at depth unless they use much more sophisticated visualizations, as demonstrated in this video.
Viewing full depth stats across the a selected period makes it easy to understand what is actually happening with trades. Traders can grouping depth into multiple buckets (in order example, ten buckets) and calculate total size, size imbalance, spreads, and size-weighted average bids and offers down the book, at each level of depth. They can see where the book widens and narrows, where the book is balanced, where there are size imbalances, and where orders are more mixed. They can also see how the best spread correlates to the weighted average spread across the book.
This approach is especially useful when making comparisons between different instruments. Traders can easily see anomalies in book depth across the market, and how those anomalies change over time, down to the nanosecond level.
This dashboard also enables users to see what sort of strategies other firms in the market are trading; for example, is a rival firm’s strategy focused on market making or is it continuously moving liquidity between both sides of the book? Is it sporadic in its order flow? Does it look like spoofing?
In this video, we are looking at trading activity for equities, but the system supports all asset classes and quants, traders, and compliance officers can visualize order books for fixed income, derivatives, commodities, and foreign exchange instruments with equal accuracy and depth.
Quick Start
Panopticon Demo: A Real-Time View of Order Book Depth
Traders need to understand what is happening to the order book right now – in real time – plus what has happened during the last few minutes. With Panopticon, traders can monitor for imbalances across instruments, and then investigate the latest book depth from that time onwards. It can query historic data stored in kdb+, OneTick, or virtually any other high performance data repository, or subscribe to live data streams from Kafka, Solace, Rabbit MQ, or other message buses.
When traders are monitoring a wide selection of stocks, they need to see a summary of all books along with calculated metrics to display anomalies. If they are monitoring only a few instruments, they most likely want to see them all in parallel. Panopticon supports either use case, and at any time, the user can jump from the live real time view of the order book to see any part of the trading day to examine anomalies in more detail.
Quick Start
Panopticon Demo: Build Stream Processing Applications with Zero Coding
Panopticon Streams, a stream processing engine built on the popular Apache Kafka platform, enables business users to build sophisticated Kafka data flows with no coding. Streams connects directly to a wide range of streaming and historic information sources, including Kafka, Kx kdb+, Solace, Hadoop and NoSQL sources. Streams supports critical data functions including:
- Streaming Data Prep: Combines multiple real-time streams with historic data sources
- Calculation Engine: Calculates performance metrics based on business needs
- Aggregation Driver: Combines data as needed
- Alerting Engine: Highlights anomalies against user-defined thresholds
- Integration with the Confluent Enterprise Control Center
- Expanded support for IoT environments, including manufacturing, energy/utilities, and transportation/logistics
The engine is designed to be used by people who understand their business problems. They can create their own data flows utilizing data from any number of sources and incorporate joins, aggregations, conflations, calculations, unions, merges, and alerts into their stream processing applications. They can then visualize processed data using Panopticon Visual Analytics and/or output it to Kafka, Kx kdb+, InfluxDb, or any SQL database.
Quick Start
Panopticon Demo: Monitor ATM Performance
This video demonstrates how to use visual analytics to monitor performance and profitability of a network of ATM machines. The system can monitor the number of transactions for each machine and identify machines that under-performing due to lack of supplies, paper, failed transactions, and/or funds. The dashboards also utilize real time data from the ATM network to help managers identify cases of potential fraud, including card cloning.
Quick Start
Panopticon Explainer: Introduction to Stream Processing
Altair Panopticon Streams is a sophisticated stream processing engine that leverages the agility, speed, and power of the Kafka Streams framework and Apache Kafka. Streams enables business users to design and deploy new data flows using a standard web browser. Simply point and click to draw the data flow. Subscribe to streaming data inputs, including Kafka topics, plus non-Kafka streaming sources like message buses, web sockets, CEP engines, ticker plants, and market data feeds. Retrieve historical data from tick databases, time series databases, SQL row stores, column stores, NoSQL, New SQL, and restful web services. Create alerts based on performance metrics against defined thresholds and output processed data to Kafka topics, to email, or write to databases like kdb+, InfluxDb, or any SQL database.
Streams supports key data operations, including:
- Join and Union data streams and tables
- Aggregate and conflate streams of data
- Perform calculations
- Filter and Branch streams
Panopticon Streams works beautifully with Panopticon Visual Analytics to create a flexible and highly capable streaming analytics platform.
Product Overview Videos
Panopticon Explainer: Introduction to Panopticon Streaming Analytics
Managing critical IoT, telecommunications, and energy infrastructures requires real-time insight into massive amounts of information. Business analysts and engineers can’t wait for end-of-day reports to make decisions that directly affect their operations. They must be able to see and understand what is happening in real time – as it happens. They must also be able to examine all the events leading up a problem in fantastic detail.
Altair Panopticon provides people working for the world’s largest corporations with the tools they need to build and deploy their own real-time analytics applications. With Panopticon, engineers and analysts can spot emerging trends, clusters, and outliers in seconds. They can also rewind and look at every single step in a series of events with nanosecond accuracy. Panopticon handles data directly from any data source you’re likely to use, including real-time message buses, time series database, CEP engines, SQL databases, and Big Data repositories.
Product Overview Videos
Panopticon Demo: Monitor IoT Sensors with Control Charts
Panopticon enables organizations to monitor and analyze real-time data streaming in from a wide variety of IoT sensors in industrial applications.
Quick Start
Panopticon Demo: Monitor and Analyze Trading Profit and Loss in Real Time
The ability to analyze profitability during the trading day is a major advantage for firms engaged in electronic or high frequency trading. Traders can take corrective action like changes to strategy and execution venue selection as soon as they spot an issue that may drag trading into loss territory for the day.
The Panopticon Streaming Analytics Platform enables buy side and sell side firms to connect to virtually any data source, including kdb+, Kafka, InfluxDB, OneTick, and Solace (as well as virtually all other sources commonly deployed in electronic trading infrastructures). They can then visualize real-time streaming and historical time series data in ways that enable them to understand what exactly is happening with their profitability, what caused specific problems, and devise effective approaches to improve profits on the day.
Quick Start
Panopticon Demo: Fast Visual Analytics for Capital Markets
Altair Panopticon makes it possible to identify outliers and anomalies very quickly in massive amounts of real-time and historical trading data. The tool is designed specifically for Capital Markets applications and major firms all over the world use it to improve profitability, manage risk, monitor trading activity, detect fraud, and perform other critical functions related to trading instruments of all types.
Quick Start
Panopticon Demo: Visual Monitoring and Analysis Applied to Best Execution
Tabular displays are useful in examining top level aggregated data, but quite limited when the number of rows grows to hundreds of thousands. This is especially true when dealing with data related Best Execution; there is an enormous amount of data to be analyzed, and the analysis must be conducted in a timely manner in order to be useful.
Specialized visual analytics tools make it much easier - and faster - to slice and dice the data to identify outliers and anomalies. We use different visual techniques to look at different aspects and dimensions in the data. When we spot a problem, we can drill into the child orders to figure out what is doing wrong. For example, visual analytics makes it obvious when a venue is underperforming, and since we can see what the issue is while it is happening, based on real-time trading data, we can reallocate our order flow to compensate during the trading day. We can also do "what if" analysis and understand what would happen if we redirected flow away from a particular venue.
Rather than using our data handling infrastructure only to generate reports as required by regulators or looking at end-of-day aggregated TCA data, we can effectively monitor and analyze all trades as they are happening and modify our trading activity to optimize our profitability and maintain compliance.
Quick Start
Technical Deep Dive - Optimize Execution Quality using Cloud Data, Python and Streaming Analytics
In this webinar our panel discusses new approaches to the old problems of optimized execution, the role of new technologies including AI in improvement, and how to implement and integrate tools and technologies to build an efficient and cost-effective technology stack. This is a deep dive into the technology architecture and tools required for quants and other decision-makers involved in the trading process to optimize execution quality.
Webinars
Greenwich Associates on Improving Trading Performance
Greenwich Associates explores how electronic and high frequency trading firms can improve the performance of their trading operations using a new generation of stream processing and real-time data visualization tools.
eBooks
Analyze Aggregated Client FX Flow with Altair Panopticon
Forex markets are becoming more electronified and participants are more diversified. Combine that with the explosion of trading venues and the FX market is today more complex and fragmented than ever before.
Tutorials